def heuristic_surface(self, rfl_meas, Ls, geom):
'''Given a reflectance estimate and one or more emissive parameters,
fit a state vector.'''
glint_band = s.argmin(abs(900 - self.wl))
glint = s.mean(rfl_meas[(glint_band - 2):glint_band + 2])
water_band = s.argmin(abs(400 - self.wl))
water = s.mean(rfl_meas[(water_band - 2):water_band + 2])
if glint > 0.05 or water < glint:
glint = 0
glint = max(self.bounds[self.glint_ind][0] + eps,
min(self.bounds[self.glint_ind][1] - eps, glint))
lrfl_est = rfl_meas - glint
x = MultiComponentSurface.heuristic_surface(self, lrfl_est, Ls, geom)
x[self.glint_ind] = glint
return x
def heuristic_surface(self, rfl_meas, Ls, geom):
'''Given a reflectance estimate and one or more emissive parameters,
fit a state vector.'''
def err(z):
T, bb_frac = z
emissivity = s.ones(self.nwl, dtype=float)
Ls_est, d = emissive_radiance(emissivity, T, self.wl)
resid = Ls_est * bb_frac - Ls
return sum(resid**2)
x_surface = MultiComponentSurface.heuristic_surface(
self, rfl_meas, Ls, geom)
T, bb_frac = minimize(err, s.array([300, 0.1])).x
bb_frac = max(eps, min(bb_frac, 1.0 - eps))
T = max(self.bounds[-2][0] + eps, min(T, self.bounds[-2][1] - eps))
x_surface[self.bb_frac_ind] = bb_frac
x_surface[self.surf_temp_ind] = T
return x_surface
